Book review: Krugman, P. (2020): Arguing with Zombies, New York, NY, USA (416 pages, W.W. Norton and Company, hardcover, ISBN 978-1-324-00501-8)
Bibliographic record
Abstract
As an undergraduate student in the 1990s, Paul Krugman's work, along with that of Joseph Stiglitz, was instrumental in my studies in economics.As an instructor in the 2020s, I was excited to find that the Nobel Laureate's book Arguing with Zombies, which is mainly based on his New York Times columns, helped to make sense of the economic orientation and situation in my home province, Alberta, where the United Conservative Party (UCP) came to power in 2019.The UCP government was extremely concerned about the previous government raising the minimum hourly wage by more than C$4 in fewer than three years but showed no qualms in reducing corporate tax rates by 4 percentage points, eliminating the carbon tax and cutting spending.This approach continued through the COVID-19 pandemic, as the government cut the post-secondary budget by 20 per cent over a four-year plan, and proposed a 3 per cent wage rollback for overworked nurses in the midst of the ongoing pandemic, while announcing investments to the tune of billions of Canadian dollars in Keystone XL, a risky and unnecessary oil pipeline.Krugman's book helps us to understand how such an economic orientation, which rests on pandering to corporate interests and harming public interest, arises from zombie ideas that are promoted by rich right-wing individuals, who fund partisan think-tanks (Krugman 2020: 3), who argue that governments should create privately funded and privately managed healthcare systems, who believe that higher deficits are due to higher spending and not to lower taxes, and who insist that cutting taxes on the wealthy and the corporations induces them to work hard and invest respectively (ibid.: 195, 225 and 229).All of this is based on the fanatic appeal to free-market orthodoxy, which, according to Krugman, dies hard (ibid.: 91).This is because, starting from ECON 101 (the principles-level economics course), instructors teach students the principles of neoclassical puritanism that people are rational and free markets work, as prices move to match supply and demand (ibid.: 138).Krugman not only highlights zombie ideas, he also systematically destroys them.He states that, based on cognitive psychology and behavioural economics, people are not rational, utility maximization is a foolish idea, equilibrium is ludicrous, and perfect competition is irrelevant for many industries (ibid.: 146 and 402).Besides panning modern monetary theory as an odd doctrine rife with confusions, and upholding the case for free trade, he comes close to the ideas espoused in heterodox economics by Komlos (2019) and Reardon et al. (2018).Krugman argues that pushing for balancing the budget during a recession only makes it worse and that fears of spiralling debt during a recession are exaggerated (Krugman 2020: 6 and 204).He states that some things like social security and healthcare insurance are better provided by the government than the private sector (ibid.: 15 and 30).In the context
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.005 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.070 | 0.055 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".